docs: def pack_nbt(s):
      """
      Pack a native Python data structure into an NBT tag. Only the following
      structures and types are supported:
  
       * int
       * float
       * str
       * unicode
       * dict
  
      Additionally, arbitrary iterables are supported.
  
      Packing is not lossless. In order to avoid data loss, TAG_Long and
      TAG_Double are preferred over the less precise numerical formats.
  
      Lists and tuples may become dicts on unpacking if they were not homogenous
      during packing, as a side-effect of NBT's format. Nothing can be done
      about this.
  
      Only strings are supported as keys for dicts and other mapping types. If
      your keys are not strings, they will be coerced. (Resistance is futile.)
      """
  
      if isinstance(s, int):
          return TAG_Long(s)
      elif isinstance(s, float):
          return TAG_Double(s)
      elif isinstance(s, (str, unicode)):
          return TAG_String(s)
      elif isinstance(s, dict):
          tag = TAG_Compound()
          for k, v in s:
              v = pack_nbt(v)
              v.name = str(k)
              tag.tags.append(v)
          return tag
      elif hasattr(s, "__iter__"):
          # We arrive at a slight quandry. NBT lists must be homogenous, unlike
          # Python lists. NBT compounds work, but require unique names for every
          # entry. On the plus side, this technique should work for arbitrary
          # iterables as well.
          tags = [pack_nbt(i) for i in s]
          t = type(tags[0])
          # If we're homogenous...
          if all(t == type(i) for i in tags):
              tag = TAG_List(type=t)
              tag.tags = tags
          else:
              tag = TAG_Compound()
              for i, item in enumerate(tags):
                  item.name = str(i)
              tag.tags = tags
          return tag
      else:
          raise ValueError("Couldn't serialise type %s!" % type(s))